In the sales, marketing and copywriting industries one of the desired features of an image is the availability of copy space. Copy space generally refers to a physical place on an image where copy or text may be added when the image is used in a design of an advertisement or display of the image in sales and marketing or related material.
With the proliferation of large libraries of internet sites making digital images available to these designers and copywriters, there is a need for a system and method to quickly search these libraries for images having copy space that satisfy their design requirements.
Current techniques for identifying images with copy space or specific features include tags, which are generally text descriptors, included as part of the image metadata. The tag data must be determined before the images are uploaded to the library. The user then searches the library for all such images having tags indicating available copy space.
A disadvantage of the tagging is that each image must be viewed and then appropriately tagged when uploaded to the library. This process can be time consuming and highly susceptible to human error. Furthermore current tags are limited in the amount of information they provide. Current searches will retrieve images that simply have copy space available, but not provide an indication as to how much space is available, where it occurs in the image, etc. So, users are not easily able to identify whether a selected group of images have, for example, a large enough copy space.